Research Fellow (Machine Learning - Data-Driven Recycling of Plastics) (106621-1122) . Job Reference: 1889172

University of Warwick
December 08, 2022
Offerd Salary:£32,348 to £42,155
Working address:N/A
Contract Type:Fixed Term Contract
Working Time:Full time
Working type:N/A
Job Ref.:N/A

Vacancy Type/Job category

Research Only




£32,348 to £42,155 per annum


University of Warwick, Coventry

Vacancy Overview

Fixed Term Contract (Ending 31/03/2024), 36.5 hours per week (1.0 FTE)

The Visualisation Group at WMG are looking for a talented and highly motivated researcher to further our research on the development of machine learning methods on the development of sustainable polymer/composite manufacturing solutions in collaboration with the WMG National Polymer Processing Centre and selected industry partners.

You will contribute to a developing project portfolio in applying AI solutions to engineering and computing problems. In particular, in the area of sustainable and circular plastics, driving a step-change in capability within the UK supply chain by addressing long-term sustainability and circularity issues at the materials, manufacturing, design and end-of-life level. Highly- sustainable materials and process solutions are currently being developed at WMG's new Materials Engineering Centre using dedicated industry-leading facilities for polymers, composites and hybrid structures.

You will have a PhD in computer science or a related field. Particularly, candidates should have experience in the following areas:

• A solid foundation in deep learning methods including the computing and statistical principles that found it.

• Experience of working with pyTorch (or similar) for solving real-world problems or advancing machine learning solutions.

• The ability to process and handle data collected from diverse sensors.

• A publication records that demonstrates the above.

Experience in machine learning projects in a collaborative R&D environment (particularly in collaboration with industry) would be advantageous. This exciting role will involve close collaboration with other academics and industrial partners and there will be opportunities for training and career development.

We will provide a great range of benefits which include an attractive pension scheme, 30 days holiday plus bank holidays and Christmas closure, some fantastic savings on a wide range of products and services, and excellent learning and development opportunities.

At WMG we are committed to supporting staff to achieve their potential. We currently hold the Athena SWAN Silver Award and the University of Warwick holds an Institutional Silver Award: a national initiative that recognises the advancement of gender equality, representation, progression and success for all in academia. We are supportive of staff with caring responsibilities including a generous maternity/paternity/adoption/parental leave policy, and onsite childcare facilities. We will consider applications for employment on a part-time or other flexible working basis, even where a position is advertised as full-time, unless there are operational or other objective reasons why it is not possible to do so.

If you have not yet been awarded your PhD but are near submission or have recently submitted your PhD, any offers of employment will be made as Research Assistant on level 5 of the University grade structure (£31,411). Upon successful award of your PhD and evidence of this fact, you will be promoted to Research Fellow on the first point of the level 6 of the University grade structure (£32,348).

Interview Date - TBC

Job Description

Job Purpose

You will undertake the design and development of machine learning solutions on the HVM Catapult funded, data-driven recycling of plastics project. Support the work of the department and develop and enhance its reputation, both internally and externally. Assist the project leader and co-investigator and where appropriate, project collaborators in the successful execution of the project.

Project Specific Responsibilities

• To form an understanding of the current solutions for using data science and machine learning methods for identifying plastics.

• To analyse and process data that has been captured (by other researchers on the project) from a variety of sensors.

• To design and develop novel machine learning solutions.

• To publish methods and results in relevant fora.

Principal Accountabilities

Research and Scholarship

1. Help establish a sound research base within the department in order to assist the development of research objectives and proposals for own or joint research.

2. Conduct individual and collaborative research projects.

3. Write up research work for publication.

4. Translate knowledge of advances in the subject area into research activity.

5. May contribute to preparing proposals and applications to external bodies, e.g. for funding and contractual purposes, to support a developing research agenda.

6. May present information on research progress and outcomes to bodies supervising research, e.g. steering groups.

7. May contribute to the preparation of papers for steering groups and other bodies.

8. Communicate complex information (orally and in writing) and material of a specialist or highly technical nature.

9. Continually update own knowledge and understanding in field or specialism.

Teaching and Learning Support

1. Could be expected to contribute to the teaching and learning programmes in the department.

2. Assist in the supervision of student projects and the development of student research skills.

3. May be involved in the assessment of student knowledge and supervision of projects.

Administration and Other Activities

1. May be required to attend departmental meetings and to participate (where necessary) in other committees and working groups within the department, the faculty and the University.

2. Ensure compliance with health and safety in all aspects of work.

3. Work within budget constraints.

Person Specification

The Person Specification focuses on the knowledge, skills, experience and qualifications required to undertake the role effectively. This is measured by (a) Application Form, (b) Test/Exercise, (c) Interview, (d) Presentation.

Essential Criteria 1

Good honours degree and possession of a PhD or equivalent doctoral qualification in a relevant discipline (computer science or related). Nearing completion of PhD or equivalent will be appointed at Research Assistant level until awarded. (a)

Essential Criteria 2

Demonstrable experience with machine learning methods for solving real-world problems and/or for advancing state-of-the-art in the field. In particular, pyTorch.(a,c,d)

Essential Criteria 3

Experience in handling data. The ability to process, analysis and prepare data for the use in machine learning applications. (a,c,d)

Essential Criteria 4

Proven ability in research and evidence of quality research output in relevant field. (a,c,d)

Essential Criteria 5

A developing research profile with the ability to publish and/or produce high quality research output. (a,c)

Essential Criteria 6

Sufficient breadth or depth of specialist knowledge in the discipline and of research methods and techniques to work within established research programmes. (a,c,d)

Essential Criteria 7

Ability or potential to contribute to the development of funding proposals in order to generate external funding to support research projects. (a,c)

Essential Criteria 8

An understanding of equal opportunity issues as they may impact on areas of research content. (a,c)

Essential Criteria 9

Good effective communication (oral and written) skills, presentation and training skills. (a,c,d)

Essential Criteria 10

Good interpersonal skills. (a,c)

Essential Criteria 11

Ability and willingness to work as a member of a team and contribute positively to a collegial team environment and to be able to work independently. (a,c)

Essential Criteria 12

Ability to initiate, plan organise, implement and deliver programmes of work to tight deadlines. (a,c)

Desirable Criteria 1

Ability to write research reports and papers in styles accessible to both academic and, where relevant, industry audiences. (a,c)

Further Particulars

For further information about the University of Warwick, please read our University Further Particulars.

For further information about the department, please visit the departmental website.

For further information on the WMG centre High Value Manufacturing Catapult, please see our website at WMG :: High Value Manufacturing Catapult (

We believe there should be no barriers to continuing education, and we strive to ensure that the future workforce has the skills they need to become the UK's upcoming engineers and inventors.

Our unique approach to undergraduate education enables full-time students, Higher Apprentices, and full-time employees to gain an engineering degree.

Our teaching staff deliver educational programmes not just at Warwick, but internationally, and the knowledge we can leverage from our research excellence enables our students to reach their highest possible standards.

Full details of our range of undergraduate and Degree Apprenticeships can be found via this link.

If you would like further information about the HEA accreditation or APPTE requirements, these links should help.

Right to work in the UK If you do not yet have the right to work in the UK and/or are seeking sponsorship for a Skilled Worker visa in the UK points-based immigration system please click on this link which contains further information about obtaining right to work in the UK and details about eligibility for sponsorship for a Skilled Worker Visa.

Warwick is committed to building an organisation of mutual respect and dignity, promoting a welcoming, diverse and inclusive working and learning environment. We recognise that everyone is different in a variety of visible and non-visible ways, and that those differences are to be recognised, respected, and valued. Where possible, we go beyond legislation to provide a place where everyone can thrive, supporting all staff to achieve their full potential. We aspire to remove economic, social and cultural barriers that may otherwise prevent people from succeeding.

We therefore welcome and encourage applications from all communities regardless of culture, background, age, disability, sex/gender, gender identity or expression, ethnicity, religion/belief, or sexual or romantic orientation. To find out more about our social inclusion work at Warwick visit our webpages here.

Recruitment of Ex-Offenders Policy

As an organisation using the (DBS) Disclosure and Barring Service to assess applicants' suitability for positions of trust, the University of Warwick complies with the DBS Code of Practice and undertakes not to discriminate unfairly against any subject of a Disclosure on the basis of a conviction or other information revealed. More information is available on the University's Vacancy pages and applicants may request a copy of the DBS Code of Practice.

Closing Date

8 Dec 2022

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